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Construction and analysis of subdivision schemes from a linear algebra perspective.
No full textSubdivision schemes are efficient tools for generating smooth curves and surfaces as limit of an iterative algorithm based on simple refinement rules starting from few control points defining a polyline or a mesh. Aim of this thesis is to give a complete framework regarding the tools used for the analysis of subdivision schemes and to exploit them to construct new subdivision schemes. We focus our attention on some linear algebra structures that allow to give an exhaustive characterization on the analysis of convergence and smoothness of the limit curves and surfaces produced. Moreover, we propose general sufficient conditions to check the convergence of non-stationary subdivision schemes on arbitrary manifold topology meshes, exploiting the eigenproperties of a block-circulant matrix. These linear algebra tools are fundamental for the construction and analysis of subdivision schemes on arbitrary manifold topology meshes. The use of this kind of meshes is extremely important: regular meshes do not allow us to design the complex models used in computer aided design as well as in biomedical imaging segmentation. Moreover, non-stationary subdivision schemes allow us to design particular shapes such as ellipsoids and tori, thanks to their capability of generating exponential polynomials. In the univariate setting, to work out necessary and sufficient conditions for the Cr continuity of a subdivision scheme, we should exploit the joint spectral radius of a set of matrices
Security in Internet of Things: networked smart objects.
No full textInternet of Things (IoT) is an innovative paradigm approaching both industries and humans every-day life. It refers to the networked interconnection of every-day objects, which are equipped with ubiquitous intelligence. It not only aims at increasing the ubiquity of the Internet, but also at leading towards a highly distributed network of devices communicating with human beings as well as with other devices. Thanks to rapid advances in underlying technologies, IoT is opening valuable opportunities for a large number of novel applications, that promise to improve the quality of humans lives, facilitating the exchange of services.
In this scenario, security represents a crucial aspect to be addressed, due to the high level of heterogeneity of the involved devices and to the sensibility of the managed information. Moreover, a system architecture should be established, before the IoT is fully operable in an efficient, scalable and interoperable manner.
The main goal of this PhD thesis concerns the design and the implementation of a secure and distributed middleware platform tailored to IoT application domains. The effectiveness of the proposed solution is evaluated by means of a prototype and real case studies
Spectral features of matrix-sequences, GLT, symbol, and application in preconditioning Krylov methods, image deblurring, and multigrid algorithms.
No full textThe final purpose of any scientific discipline can be regarded as the solution of real-world problems. With this aim, a mathematical modeling of the considered phenomenon is often compulsory. Closed-form solutions of the arising functional equations are usually not available and numerical discretization techniques are required. In this setting, the discretization of an infinite-dimensional linear equation via some linear approximation method, leads to a sequence of linear systems of increasing dimension whose coefficient matrices could inherit a structure from the continuous problem. For instance, the numerical approximation by local methods of constant or nonconstant coefficients systems of Partial Differential Equations (PDEs) over multidimensional domains, gives rise to multilevel block Toeplitz or to Generalized Locally Toeplitz (GLT) sequences, respectively. In the context of structured matrices, the convergence properties of iterative methods, like multigrid or preconditioned Krylov techniques, are strictly related to the notion of symbol, a function whose role relies in describing the asymptotical distribution of the spectrum.
This thesis can be seen as a byproduct of the combined use of powerful tools like symbol, spectral distribution, and GLT, when dealing with the numerical solution of structured linear systems. We approach such an issue both from a theoretical and practical viewpoint. On the one hand, we enlarge some known spectral distribution tools by proving the eigenvalue distribution of matrix-sequences obtained as combination of some algebraic operations on multilevel block Toeplitz matrices. On the other hand, we take advantage of the obtained results for designing efficient preconditioning techniques. Moreover, we focus on the numerical solution of structured linear systems coming from the following applications: image deblurring, fractional diffusion equations, and coupled PDEs. A spectral analysis of the arising structured sequences allows us either to study the convergence and predict the behavior of preconditioned Krylov and multigrid methods applied to the coefficient matrices, or to design effective preconditioners and multigrid solvers for the associated linear systems
Evaluation by optical and soil sensors of forest seedlings grown in controlled conditions under low-energy lighting (LED)
No full textIntroduction
LED lights have a lower environmental impact than traditional lights due to a series of factors such as their wavelength specificity and narrow bandwidth, high energy-conversion efficiency, small volume, longer life, low thermal energy output. Concerning plant growth, the uses of LED lights provide specific wavelength as well as the possibility to adjust light intensity/quality. The increasingly need to reduce energy consumption worldwide, raised the necessity to improve LED lights use. The present study aims to 1) examine the effect of different LED light spectra on forest seedlings growth of different species, in order to define a species-specific cultivation protocols under optimal plant growth spectrum to enhance plant growth performance 2) compare direct measurements with indirect method by optical sensors system for automatic plant phenotyping 3) develop soil sensors system for automatic measurements of optimal soil water content. The plant species analysed, widely used in protective and productive planted forests, were: Scots pine Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies L.), Beech (Fagus sylvatica L.), Holm oak (Quercus ilex L.), Pomegranate (Punica granatum L.), Strawberry-tree (Arbutus unedo L.), Firetree (Morella faya (Ait.) Wilbur), Sanguinho (Frangula azorica Tutin) and Azores laurel cherry Prunus azorica (Hort. ex Mouillef.).
Materials and methods
Seeds of almost all investigated species were pre-treated to removal dormancy before sowing in mini-plug container. Trays were placed in growth chambers (12-14-16 h photoperiod, 110 ±10 μmol m-2 s-1 PAR, temperature 20-30°C, humidity 55-80%). Seedlings were left to grow for 4-8 weeks under G2, AP67, AP67-3L, NS1, AP67tube LED light (Valoya) and Fluorescent light (FL). The LED lamps used in this study emitted a continuous spectrum thanks to a mixture of blue, green, red and far-red LEDs. Direct measurements of plant height, root length, shoot and root biomass were carried. In order to estimate total root length, roots were scanned and analyzed by WinRHIZO Pro V. 2007d. Non-destructive analysis was carried by measuring Greenness (percentage of shoot cover projected on tray ground) and Plant height by optical sensors. Greenness data were obtained by a series of images acquired by specific developed Optical sensors system (ACREO) and analysed by uEyeDualcam software. After that HeightMap software recalculate greenness using uEyeDualCam settings output and create a plant height map (cm) of the tray conferring a value to the pixel of the selected images.
Plant height data, manually taken during the growth period, were used to find a relationship with plant biomass and with data from images analysed by uEyeDualcam HeightMap software (ACREO). Electronic soil sensors tested in the trays with and without seedlings helding watering for two weeks in order to evaluate the soil water content measurements efficiency of the soil. Soil water content measurement obtained by the software “Zephyr logger” (Acreo) was compared with the SWC calculated by gravimetric measurements.
Results and discussion
The best results recorded for all studied species were under AP67, AP67-3L and G2 LED light type for all morphological parameters analysed. The lowest values among all LED light type were obtained under NS1 LED type for almost all morphological parameters. Results showed a linear increment of seedling height in time for six species (Pinus sylvestris, Picea abies, Quercus ilex, Fagus sylvatica and Punica granatum) and for all different light types. P. sylvestris, P. abies and A. unedo showed interesting results in root length mainly under G2 LED type. A. unedo showed slightly higher biomass values for seedlings growth under G2 LED light type, in particular for root and leaves biomass. The lowest values among all LED light type were obtained under NS1 LED type for almost all studied morphological parameters. The low seeds germination of Morella faya species was detected under all different LED light types. In particular, Morella faya seeds did not show any germination under AP67-3L LED light type. Analysis of the total dry mass increment (g; shoot + root) showed the highest values for seedlings growth under AP67 light type (bar) among all LED light types and control light. The lowest values of total dry mass increment were measured for seedlings growth under AP67 tube. A high heterogeneity in seed germination and plant growth was observed. Concerning the optical analysis results, relation between greenness and seedling biomass showed good correlation for all species until the tray was fully covered. Instead, the relation between seedling height and biomass showed good results with the two broad-leaved species but no relation was found for the two needle-leaved species. Indeed, the constant height of P. abies (L.) and P. sylvestris (L.) because internodes elongation did not occur during the consecutive emissions of new leaves, did not relate to the continuous increment of seedling biomass. This is probably due to the specie-specific characteristic. Thus, the best regression model to explain the relationship between direct biomass data and indirect measurements was based on parameters such as plant height, for broad-leaved species, and plant greenness for needle-leaved species. The main result of our study is that the relevance of relations between non-destructive parameters and forest seedlings growth is species specific.
Conclusion
- Plant growth performance with LED light is specie-specific.
- LED lights represent an efficient and valid alternative to the fluorescent light.
- The best performance for all studied species are observed with AP67, AP67-3L and G2 LED light type whereas NS1 LED type seems to not be suitable for this use.
- G2 gave some good results but due to its higher percentage of far-red/red, it can cause operators’ eyes fatigue and could interfere with optical measurements such as greenness.
- Finally, AP67 and AP67-3L LED type could represent the best option for a standard cultivation protocol.
Data collected confirm that optical system (sensors and software) could represent a robust method to measure plant phenotype as alternative to the traditionally used destructive methods.
Protocol of seed germination developed during the present study and applied to Morella faya seeds, showed good results for the ex-situ plant species conservation objective.
Electronic soil sensors represent a good system to monitor the water content in the soil and when they are used in combination with LED light, and optical sensors the result is a complex system characterized by high level of cost-effectiveness coupled with a good possibility to save energy consumption and reduce pollutio
Human induced pluripotent stem cells as a source of insulin-producing cells for cell therapy of diabetes
No full textBACKGROUND
New sources of insulin-secreting cells are strongly required for the cure of diabetes.
Recent successes in differentiating embryonic stem cells, in combination with the discovery that it is possible to derive human induced pluripotent stem cells (iPSC) from somatic cells, have raised the possibility that patient-specific β cells might be derived from patients through cell reprogramming and differentiation.
AIMS
In this study, we aimed to obtain insulin-producing cells from human iPSC and test their ability to secrete insulin in vivo.
METHODS:
Human iPSC, derived from both fetal and adult fibroblasts, were differentiated in vitro into pancreas-committed cells and their ability to secrete insulin was measured. iPSCderived cells at two different stages of differentiation (posterior foregut and endocrine cells) were transplanted into immunodeficient mice to test their ability to engraft, differentiate and secrete insulin.
RESULTS:
IPSC were shown to differentiate into insulin-producing cells in vitro, following the stages of pancreatic organogenesis. At the end of the differentiation, the production of INSULIN mRNA was highly increased and up to 14% of the cell population became insulin-positive. Terminally differentiated cells also produced C-peptide in vitro in both basal and stimulated conditions. In vivo, mice transplanted with pancreatic cells secreted human C-peptide in response to glucose stimulus, but transplanted cells were observed to lose insulin secretion capacity during the time. At histological evaluation, the grafts were composed of a mixed population of cells containing mature pancreatic cells, but also pluripotent cells and rare neuronal cells.
CONCLUSION:
These data overall suggest that human iPSC have the potential to generate insulinproducing cells and that these differentiated cells can engraft and secrete insulin in vivo
A multi-scale study of fibrin gels formation: from the early phases to the final network.
No full textFibrin gel polymerization, key element of blood coagulation, produces the network inside which platelets and other blood components are trapped, forming the hemostatic plug that stops bleeding. As fully biocompatible materials with extraordinary mechanical properties, fibrin gels are ideal substrates for many biotechnological applications.
By studying the early phases of polymerization, using simultaneous Small Angle X-ray Scattering and Wide Angle Light Scattering, we defined a new polymerization model in which single-bonded "Y Ladder" polymers rapidly elongate before undergoing a delayed transition to the traditional double-stranded fibrils.
Completely formed fibrin gel appears as a fractal collection of straight fibers, almost monodisperse in diameter and connected together at nodal points with a branching order 3-4. Taking into account these features, we implemented a simple iterative algorithm able to generate in silico gels. The resulting 3D network resembles real fibrin gels and can be sketched as an assembly of densely packed fractal blobs. Using this model we refined the analytical expression of the form factor which is capable of accurately fitting the Light Scattering data, giving the gels' structural parameters.
By globally fitting Low Angle Elastic Light Scattering data with the refined form factor and Turbidimetry data with a function obtained by angularly integrating the scattering form factor, all the parameters characterizing the gel can be robustly recovered.
Finally we have also developed a 2D method for the determination of the gel pore size that analyze thin stacks of randomly sampled thresholded 3D confocal images
Text localization and recognition in natural scene images
No full textText localization and recognition (text spotting) in natural scene images is an interesting task that finds many practical applications. Algorithms for text spotting may be used in helping visually impaired subjects during navigation in unknown environments; building autonomous driving systems that automatically avoid collisions with pedestrians or automatically identify speed limits and warn the driver about possible infractions that are being committed; and to ease or solve some tedious and repetitive data entry tasks that are still manually carried out by humans. While Optical Character Recognition (OCR) from scanned documents is a solved problem, the same cannot be said for text spotting in natural images. In fact, this latest class of images contains plenty of difficult situations that algorithms for text spotting need to deal with in order to reach acceptable recognition rates. During my PhD research I focused my studies on the development of novel systems for text localization and recognition in natural scene images. The two main works that I have presented during these three years of PhD studies are presented in this thesis: (i) in my first work I propose a hybrid system which exploits the key ideas of region-based and connected components (CC)-based text localization approaches to localize uncommon fonts and writings in natural images; (ii) in my second work I describe a novel deep-based system which exploits Convolutional Neural Networks and enhanced stable CC to achieve good text spotting results on challenging data sets. During the development of both these methods, my focus has always been on maintaining an acceptable computational complexity and a high reproducibility of the achieved results
Studio della qualità dell'aria indoor in un'area altamente inquinata della Sicilia
No full textBoth indoor and outdoor air pollution have significant impact and risk for human health. Fossil fuel burning by power stations, chemical industry and motor vehicle emission represent major outdoor air polluting sources which may result in health effects.
Outdoor and indoor air pollution have been implicated in the epidemic of asthma and respiratory problems affecting up to 15% of the populations, with some complaints, such as allergic rhinitis, possibly exceeding 50%.
Studies in Sicily have confirmed a high prevalence of respiratory diseases. However, while the relation to outdoor pollution was to some extent explored, the role of indoor pollution was not.
This project assessed a sample of the Gela communities in the Mediterranean area of south Sicily (Gela, Niscemi, Mazzarino, Butera) for known respiratory diseases, using standardized scientific questionnaires, and making measurements of lung function and level and type of allergies of these populations. Specific measurements of indoor air pollution were made while routine data for outdoor air pollution were obtained.
This project aimed to re-assess and compare the situation of respiratory health determining the relationship between exposure to pollutants and health effects, also attempting to establish risk factors related to lifestyle, and the type of pollution, with a special innovative focus on sources of indoor air pollution.
Such data will be of importance in planning and regulating sources of both indoor and outdoor air pollution, and taking the necessary measures to reduce the impact on human health
